Digital Rights Management: Improving Online Digital Images Copy Rights Management through an Enhanced Least Significant Bit Steganographic Algorithm

Abstract

Digital media no doubt presents numerous advantages compared to the traditional analog media. Of the most importance is the fact that digital content (images, graphics, audio and video) can be easily copied, transmitted, retrieved and distributed over private and open access networks. The global availability of the internet- certainly the most impactful information exchange tool today- plus the numerous file sharing tools freely available have made the distribution of copyrighted digital media files simple and straightforward. Duplication of exact copies of original images, for example can be easily done and circulated without authentication. As much as this is an advantage in trying to enhance sharing of information, it certainly creates problems of ownership and authenticity and digital rights protection. There already exists copyright laws that provide for protection of all online content but the task of continuously guarding the web and correctly identifying those that infringe against these laws is increasingly becoming enormous. There is therefore need to continuously invest in development of new technologies and algorithms that will make it more and more difficult to illegally copy or use someone else content. To improve security of copyrighted online digital images, this paper proposes the use of an enhanced LSB steganographic algorithm that employs a selective and randomized approach in picking specific number of target image bits to swap with the owners signature authentication bits using a pseudo random number generator (PRNG). The carefully selected password seed is used to determine the set of selected numbers used for targeting specific image bits for the signature hiding. An experimental design is setup to determine the effectiveness of the method by comparing and analyzing the stego images’ statistical characteristics and the ability of steganalysis methods to detect the hidden signature. The experimental results indicate improved levels of imperceptibility and hence improved security against illegal copying.